According to IDG’s 2020 Cloud Computing Study, 92% of organizations have at least some sort of cloud footprint in regard to their IT environment. Therefore, traditional cloud security approaches must evolve to keep up with the dynamic infrastructure and challenges that cloud environments present – most notably, the inundation of data insights generated within the cloud.
More than one-third of IT security managers and security analysts ignore threat alerts when the queue is full. This is a common issue that is driving the high demand for machine learning-based analytics, as it helps security teams sift through massive amounts of data to prioritize risks and vulnerabilities and make more informed decisions
However, a word of caution when using machine learning-based technology: the age-old garbage-in, garbage-out applies to security-focused machine learning engines. If your data is bad, then your machine learning tools will be insufficient, making your security infrastructure vulnerable to attack and putting your organization at risk for a wide-spread security breach. Read More
Tag Archives: Cyber
The U.S. Government Needs to Overhaul Cybersecurity. Here’s How.
After the 2015 hack of the U.S. Office of Personnel Management, the SolarWinds breach, and—just weeks after SolarWinds—the latest Microsoft breach, it is by now clear that the U.S. federal government is woefully unprepared in matters of cybersecurity. Following the SolarWinds intrusion, White House leaders have called for a comprehensive cybersecurity overhaul to better protect U.S. critical infrastructure and data, and the Biden administration plans to release a new executive order to this end.
What should this reinvestment in cybersecurity look like? Although the United States is the home of many top cybersecurity companies, the U.S. government is behind where it should be both in technology modernization and in mindset. Best-in-class cyberdefense technologies have been available on the market for years, yet the U.S. government has failed to adopt them, opting instead to treat cybersecurity like a counterintelligence problem and focusing most of its resources on detection. Yet the government’s massive perimeter detection technology, Einstein, failed to detect the SolarWinds intrusion—which lays bare the inadequacy of this approach. Read More
Preparing for AI-enabled cyberattacks
Artificial intelligence in the hands of cybercriminals poses an existential threat to organizations—IT security teams need “defensive AI” to fight back.
Cyberattacks continue to grow in prevalence and sophistication. With the ability to disrupt business operations, wipe out critical data, and cause reputational damage, they pose an existential threat to businesses, critical services, and infrastructure. Today’s new wave of attacks is outsmarting and outpacing humans, and even starting to incorporate artificial intelligence (AI). What’s known as “offensive AI” will enable cybercriminals to direct targeted attacks at unprecedented speed and scale while flying under the radar of traditional, rule-based detection tools.
Some of the world’s largest and most trusted organizations have already fallen victim to damaging cyberattacks, undermining their ability to safeguard critical data. With offensive AI on the horizon, organizations need to adopt new defenses to fight back: the battle of algorithms has begun. Read More
12 Ways to Hack 2FA
Hackers are finding ways to hide inside Apple’s walled garden
The iPhone’s locked-down approach to security is spreading, but advanced hackers have found that higher barriers are great for avoiding capture.
You’ve heard of Apple’s famous walled garden, the tightly controlled tech ecosystem that gives the company unique control of features and security. All apps go through a strict Apple approval process, they are confined so sensitive information isn’t gathered on the phone, and developers are locked out of places they’d be able to get into in other systems. The barriers are so high now that it’s probably more accurate to think of it as a castle wall.
Virtually every expert agrees that the locked-down nature of iOS has solved some fundamental security problems, and that with these restrictions in place, the iPhone succeeds spectacularly in keeping almost all the usual bad guys out. But when the most advanced hackers do succeed in breaking in, something strange happens: Apple’s extraordinary defenses end up protecting the attackers themselves. Read More
Google says it’s too easy for hackers to find new security flaws
Attackers are exploiting the same types of software vulnerabilities over and over again, because companies often miss the forest for the trees.
In December 2018, researchers at Google detected a group of hackers with their sights set on Microsoft’s Internet Explorer. Even though new development was shut down two years earlier it’s such a common browser that if you can find a way to hack it, you’ve got a potential open door to billions of computers.
The hackers were hunting for, and finding, previously-unknown flaws, known as zero-day vulnerabilities.
Google’s security team known as Project Zero, spotlights multiple examples of zero-days, including problems that Google itself has had with its popular Chrome browser. Read More
Project Zero
- Introducing the In-the-Wild Series
- Chrome: Infinity Bug
- Chrome Exploits
- Android Exploits
- Android Post-Exploitation
- Windows Exploits
Use real-time anomaly detection reference patterns to combat fraud
Businesses of every size and shape have a need to better understand their customers, their systems, and the impact of external factors on their business. How rapidly businesses mitigate risks and capitalize on opportunities can set apart successful businesses from businesses that can’t keep up. Anomaly detection—or in broader terms, outlier detection—allows businesses to identify and take action on changing user needs, detect and mitigate malignant actors and behaviors, and take preventive actions to reduce costly repairs.
The speed at which businesses identify anomalies can have a big impact on response times, and in turn, associated costs.
… At Google Cloud, our customer success teams have been working with an increasing number of customers to help them implement streaming anomaly detection. In working with such organizations to help them build anomaly detection systems, we realized that providing these reference patterns can significantly reduce the time to solution for those and future customers. Read More
The AI-Powered Cybersecurity Arms Race and its Perils
The advancement in the field of artificial intelligence (AI) is still one of the most important technological achievements in recent history. The prominence and prevalence of machine learning and deep learning algorithms of all types, being able to unearth and infer valuable conclusions about the world surrounding us without being explicitly programmed to do so, has sparked both the imagination and primordial fears of the general public.
The cybersecurity industry is no exception. It seems that wherever you go, you can’t find a cybersecurity vendor that doesn’t rely, to some extent, on Natural Language Processing (NLP), computer vision, neural networks, or other technology strains of what could be broadly categorised or branded as ‘AI’. Read More
Top 8 Machine Learning Tools For Cybersecurity
In the present scenario, techniques like AI and machine learning are involved in almost all sectors. These techniques help organisations by various means, starting from getting insights from raw data to predicting future outcomes, and more.
Focussing all the benefits of AI and ML, the utilisation of machine learning techniques in cybersecurity has been started only a few years ago and still at a niche stage. AI in cybersecurity can help in various ways, such as identifying malicious codes, self-training and other such. Read More
Knowledge in the grey zone: AI and cybersecurity
Cybersecurity protects citizens and society from harm perpetrated through computer networks. Its task is made ever more complex by the diversity of actors—criminals, spies, militaries, hacktivists, firms—operating in global information networks, so that cybersecurity is intimately entangled with the so-called grey zone of conflict between war and peace in the early twenty-first century. To counter cyber threats from this environment, cybersecurity is turning to artificial intelligence and machine learning (AI) to mitigate anomalous behaviours in cyberspace. This article argues that AI algorithms create new modes and sites of cybersecurity knowledge production through hybrid assemblages of humans and nonhumans. It concludes by looking beyond ‘everyday’ cybersecurity to military and intelligence use of AI and asks what is at stake in the automation of cybersecurity. Read More
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